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Version: 0.13.1

DataHub Quickstart Guide

Managed DataHub

This guide provides instructions on deploying the open source DataHub locally. If you're interested in a managed version, Acryl Data provides a fully managed, premium version of DataHub.
Get Started with Managed DataHub


  • Install Docker and Docker Compose v2 for your platform.

    WindowDocker Desktop
    MacDocker Desktop
    LinuxDocker for Linux and Docker Compose
  • Launch the Docker engine from command line or the desktop app.

  • Ensure you have Python 3.8+ installed & configured. (Check using python3 --version).

Docker Resource Allocation

Make sure to allocate enough hardware resources for Docker engine.
Tested & confirmed config: 2 CPUs, 8GB RAM, 2GB Swap area, and 10GB disk space.

Install the DataHub CLI

python3 -m pip install --upgrade pip wheel setuptools
python3 -m pip install --upgrade acryl-datahub
datahub version
Command Not Found

If you see command not found, try running cli commands like python3 -m datahub version.
Note that DataHub CLI does not support Python 2.x.

Start DataHub

Run the following CLI command from your terminal.

datahub docker quickstart

This will deploy a DataHub instance using docker-compose. If you are curious, the docker-compose.yaml file is downloaded to your home directory under the .datahub/quickstart directory.

If things go well, you should see messages like the ones below:

Fetching docker-compose file from GitHub
Pulling docker images...
Finished pulling docker images!

[+] Running 11/11
⠿ Container zookeeper Running 0.0s
⠿ Container elasticsearch Running 0.0s
⠿ Container broker Running 0.0s
⠿ Container schema-registry Running 0.0s
⠿ Container elasticsearch-setup Started 0.7s
⠿ Container kafka-setup Started 0.7s
⠿ Container mysql Running 0.0s
⠿ Container datahub-gms Running 0.0s
⠿ Container mysql-setup Started 0.7s
⠿ Container datahub-datahub-actions-1 Running 0.0s
⠿ Container datahub-frontend-react Running 0.0s
✔ DataHub is now running
Ingest some demo data using `datahub docker ingest-sample-data`,
or head to http://localhost:9002 (username: datahub, password: datahub) to play around with the frontend.
Need support? Get in touch on Slack:
Mac M1/M2

On Mac computers with Apple Silicon (M1, M2 etc.), you might see an error like no matching manifest for linux/arm64/v8 in the manifest list entries. This typically means that the datahub cli was not able to detect that you are running it on Apple Silicon. To resolve this issue, override the default architecture detection by issuing datahub docker quickstart --arch m1

Sign In

Upon completion of this step, you should be able to navigate to the DataHub UI at http://localhost:9002 in your browser. You can sign in using the default credentials below.

username: datahub
password: datahub

To change the default credentials, please refer to Change the default user datahub in quickstart.

Ingest Sample Data

To ingest the sample metadata, run the following CLI command from your terminal

datahub docker ingest-sample-data
Token Authentication

If you've enabled Metadata Service Authentication, you'll need to provide a Personal Access Token using the --token <token> parameter in the command.

That's it! Now feel free to play around with DataHub!

Common Operations

Stop DataHub

To stop DataHub's quickstart, you can issue the following command.

datahub docker quickstart --stop

Reset DataHub

To cleanse DataHub of all of its state (e.g. before ingesting your own), you can use the CLI nuke command.

datahub docker nuke

Upgrade DataHub

If you have been testing DataHub locally, a new version of DataHub got released and you want to try the new version then you can just issue the quickstart command again. It will pull down newer images and restart your instance without losing any data.

datahub docker quickstart

Customize installation

If you would like to customize the DataHub installation further, please download the docker-compose.yaml used by the cli tool, modify it as necessary and deploy DataHub by passing the downloaded docker-compose file:

datahub docker quickstart --quickstart-compose-file <path to compose file>

Back up DataHub

The quickstart image is not recommended for use as a production instance.
However, in case you want to take a backup of your current quickstart state (e.g. you have a demo to your company coming up and you want to create a copy of the quickstart data so you can restore it at a future date), you can supply the --backup flag to quickstart.

datahub docker quickstart --backup

This will take a backup of your MySQL image and write it by default to your ~/.datahub/quickstart/ directory as the file backup.sql.


Note that the Quickstart backup does not include any timeseries data (dataset statistics, profiles, etc.), so you will lose that information if you delete all your indexes and restore from this backup.

Restore DataHub

As you might imagine, these backups are restore-able. The following section describes a few different options you have to restore your backup.

To restore a previous backup, run the following command:

datahub docker quickstart --restore

This command will pick up the backup.sql file located under ~/.datahub/quickstart and restore your primary database as well as the elasticsearch indexes with it.

To supply a specific backup file, use the --restore-file option.

datahub docker quickstart --restore --restore-file /home/my_user/datahub_backups/quickstart_backup_2002_22_01.sql

Next Steps

Move To Production


Quickstart is not intended for a production environment. We recommend deploying DataHub to production using Kubernetes. We provide helpful Helm Charts to help you quickly get up and running. Check out Deploying DataHub to Kubernetes for a step-by-step walkthrough.

The quickstart method of running DataHub is intended for local development and a quick way to experience the features that DataHub has to offer. It is not intended for a production environment. This recommendation is based on the following points.

Default Credentials

quickstart uses docker compose configuration which includes default credentials for both DataHub, and it's underlying prerequisite data stores, such as MySQL. Additionally, other components are unauthenticated out of the box. This is a design choice to make development easier and is not best practice for a production environment.

Exposed Ports

DataHub's services, and it's backend data stores use the docker default behavior of binding to all interface addresses. This makes it useful for development but is not recommended in a production environment.

Performance & Management

quickstart is limited by the resources available on a single host, there is no ability to scale horizontally. Rollout of new versions often requires downtime and the configuration is largely pre-determined and not easily managed. Lastly, by default, quickstart follows the most recent builds forcing updates to the latest released and unreleased builds.